Sinusoidal representation has been widely applied to speech modification, low bit rate speech and audio coding. Usually, speech signal is analyzed and synthesized using the overlap-add algorithm or the peak-picking algorithm. But the overlap-add algorithm is well known for high computational complexity and the peak-picking algorithm cannot track the transient and syllabic variation well. In this letter, both algorithms are applied to speech analysis/synthesis. Peaks are picked in the curve of power spectral density for speech signal; the frequencies corresponding to these peaks are arranged according to the descending orders of their corresponding power spectral densities. These frequencies are regarded as the candidate frequencies to determine the corresponding amplitudes and initial phases according to the least mean square error criterion. The summation of the extracted sinusoidal components is used to successively approach the original speech signal. The results show that the proposed algorithm can track the transient and syllabic variation and can attain the good synthesized speech signal with low computational complexity.

We propose a new class of binary nonlinear codes of constant weights derived from a permutation representation of a group that is given by a combinatorial definition such as Cayley graphs of a group. These codes are constructed by the following direct interpretation method from a group: (1) take one discrete group whose elements are defined by generators and their relations, such as those in the form of Cayley graphs; and (2) embedding the group into a binary space using some of their permutation representations by providing the generators with realization of permutations of some terms. The proposed codes are endowed with some good characteristics as follows: (a) we can easily learn information about the distances of the obtained codes, and moreover, (b) we can establish a decoding method for them that can correct random errors whose distances from code words are less than half of the minimum distances achieved using only parity checking procedures.

A novel evolutionary algorithm is described for designing the topology of spanning tree-based communication networks. Two specific performance objectives are dealt with: the optimum communication spanning tree problem (OCSTP), and the quadratic minimum spanning tree problem (q-MST). Improved network performance is reliably obtained when using the proposed algorithm on accepted benchmark instances, in comparison with the previous best-known approaches. The same methodology can be applied straightforwardly to the design of communication networks with other objectives.

In reconstructing 3-D from images based on feature points, one usually defines a triangular mesh that has these feature points as vertices and displays the scene as a polyhedron. If the scene itself is a polyhedron, however, some of the displayed edges may be inconsistent with the true shape. This paper presents a new technique for automatically eliminating such inconsistencies by using a special template. We also present a technique for removing spurious occluding edges. All the procedures do not require any thresholds to be adjusted. Using real images, we demonstrate that our method has high capability to correct inconsistencies.

The radiation properties of oscillating electric dipoles are studied theoretically for three and four layered systems including a single metallic slab based on angular spectrum representation of vector spherical waves. One of the remarkable results obtained is the transmission energy spectrum showing strong dependence on the thickness of a dielectric layer placed between oscillating electric dipole and metallic surface, which explains the experimental results of molecular fluorescence into surface plasmon modes. The theory based on angular spectrum representation and tunneling current provides us with a clear identification of plasmonic excitation transfer, transmission loss associated with plasmon transport in metallic layer, and energy dissipation or quenching of excitation due to surface plasmon excitation at the metallic surface in relation to the characteristic complex wave number of evanescent waves.

In this paper, the previously introduced periodic Fourier transform concept is extended to a two-dimensional case. The relations between the periodic Fourier transform, harmonic series representation and Fourier integral representation are also discussed. As a simple application of the periodic Fourier transform, the scattering of a scalar wave from a finite periodic surface with weight is studied. It is shown that the scattered wave may have an extended Floquet form, which is physically considered as the sum of diffraction beams. By the small perturbation method, the first order solution is given explicitly and the scattering cross section is calculated.

This letter considers relationship between cyclic digital-to-analog converters (DACs) and iterated function systems (IFSs). We introduce the cyclic DACs as inverse systems of analog-to-digital converters in terms of one-dimensional maps. We then compare the DACs with a typical example of existing applications of IFSs: chaos game representation for analysis of DNA structures. We also present a simple test circuit of a DAC for Gray decoding based on switched capacitors and confirm the basic operation experimentally.

We propose a method for reducing the size of a share in visual secret sharing schemes. The proposed method does not cause the leakage and the loss of the original image. The quality of the recovered image is almost same as that of previous schemes.

This paper considers Quasi-Reduced ordered Multi-valued Decision Diagrams with k bits (QRMDD(k)s) to represent binary logic functions. Experimental results show relations between the values of k and the numbers of nodes, the memory sizes, the numbers of memory accesses, and area-time complexity for QRMDD(k). For many benchmark functions, the numbers of nodes and memory accesses for QRMDD(k)s are nearly equal to of the corresponding Quasi-Reduced ordered Binary Decision Diagrams (QRBDDs), and the memory sizes and the area-time complexities for QRMDD(k)s are minimum when k = 2 and k = 3-6, respectively.

In this paper, we explore a method to the problem of spoken document categorization, which is the task of automatically assigning spoken documents into a set of predetermined categories. To categorize spoken documents, subword unit representations are used as an alternative to word units generated by either keyword spotting or large vocabulary continuous speech recognition (LVCSR). An advantage of using subword acoustic unit representations to spoken document categorization is that it does not require prior knowledge about the contents of the spoken documents and addresses the out of vocabulary (OOV) problem. Moreover, this method works in reliance on the sounds of speech rather than exact orthography. The use of subword units instead of words allows approximate matching on inaccurate transcriptions, makes "sounds-like" spoken document categorization possible. We also explore the performance of our method when the training set contains both perfect and errorful phonetic transcriptions, and hope the classifiers can learn from the confusion characteristics of recognizer and pronunciation variants of words to improve the robustness of whole system. Our experiments based on both artificial and real corrupted data sets show that the proposed method is more effective and robust than the word based method.

We have developed an algorithm called the "spectral-domain-to-real-space approach" (SDRSA) to analytically calculate radiation from the two-dimensional current density distribution in microstrip line configurations where the microstrip lines are represented in the form of a three-dimensional inhomogeneous structure. The algorithm is based on the spectral-domain approach used to estimate radiation from microstrip line configurations. Calculation results obtained by using the SDRSA and the current density distribution from a quasi-TEM mode model of microstrip lines agree well with the corresponding estimations obtained by using the equivalent electric current source method and the magnetic current source method, and with the experimental results obtained in the frequency band of up to 1 GHz.

The traditional way of approaching device-level placement problems for analog layout is to explore a huge search space of absolute placement representations, where cells are allowed to illegally overlap during their moves. This paper presents a novel exploration technique for analog placement, operating on a subset of tree representations of the layout, where the typical presence of an arbitrary number of symmetry groups of devices is directly taken into account during the search of the solution space. The efficiency of the novel approach is due to the use of red-black interval trees, data structures employed to support operations on dynamic sets of intervals.

The discrete nature of data in a functional domain can generally be replaced by the global nature of data in the spectrum domain. In this paper we propose a fast procedure to detect autosymmetric function as an application of the spectrum technique. The autosymmetric function differs from the usual symmetric function and strongly relates with EXOR-based representations. It is known that many practical logical networks are autosymmetric, and this nature allows a useful functional class to realize a compact network with EXOR gates. Our procedure is able to detect autosymmetric functions quickly by using spectral coefficients. In experiments, our technique can detect the autosymmetry of most networks with a small number of checks of the spectrum.

In the image recognition problem, it is very important how we represent the image. Considering this, we propose a new representational method of images based on the stability in scale-space. In our method, the image is segmented and represented as a hierarchical region graph in scale-space. The object is represented as feature graph, which is subgraph of region graph. In detail, the region graph is defined on the image with the relation of each segment hierarchically. And the feature graph is determined based on the "life-time" of the graph of the object in scale-space. This "life-time" means how long feature graph lives when the scale parameter is increased. We apply our method to the face detection problem, which is foundmental and difficult problem in face recognition. We determine the feature graph of the frontal human face statistical point of view. We also build the face detection system using this feature graph to show how our method works efficiently.

Synergies in processing requirements and knowledge of human speech production and perception have led to a similarity of the speech signal representations used for the tasks of recognition, coding, and modification. The representations are generally composed of a description of the vocal-tract transfer function and, in the case of coding and modification, a description of the excitation signal. This paper provides an overview of commonly used representations. For coding and modification, autoregressive models represented by line spectral frequencies perform well for the vocal tract, and pitch-synchronous filter banks and modulation-domain filters perform well for the excitation. For recognition, good representations are based on a smoothed magnitude response of the vocal tract.

In this paper, a novel chrominance up-sampling algorithm for color post-processing is described. This scheme exploits so-called inter-chrominance coherence, i.e., luminance and chrominance signals share the same structural information. Usually luminance has higher spatial resolution than chrominance in compression coding standards. So the idea is to up-sample chrominance signals using the structural information extracted from the luminance.

This paper presents a method for disambiguating word senses in Korean-Japanese machine translation by using a language independent ontology. This ontology stores semantic constraints between concepts and other world knowledge, and enables a natural language processing system to resolve semantic ambiguities by making inferences with the concept network of the ontology. In order to acquire a language-independent and reasonably practical ontology in a limited time and with less manpower, we extend the existing Kadokawa thesaurus by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. The former can be obtained by converting valency information and case frames from previously-built electronic dictionaries used in machine translation. The latter can be acquired from concept co-occurrence information, which is extracted automatically from a corpus. In practical machine translation systems, our word sense disambiguation method achieved an improvement of average precision by 6.0% for Japanese analysis and by 9.2% for Korean analysis over the method without using an ontology.

In this paper, a method is proposed to construct an n-out-of-n visual secret sharing scheme for gray-scale images, for short an (n,n)-VSS-GS scheme, which is optimal in the sense of contrast and pixel expansion, i.e., resolution. It is shown that any (n,n)-VSS-GS scheme can be constructed based on the so-called polynomial representation of basis matrices treated in [15],[16]. Furthermore, it is proved that such construction can attain the optimal (n,n)-VSS-GS scheme.

A visual secret sharing scheme (VSSS) is one of secret sharing schemes for images. Droste showed the method for constructing VSSS based on basis matrices whose contrast was high. Koga, Iwamoto, and Yamamoto also proposed the method for constructing a lattice-based VSSS and its polynomial representation. It is known that many good VSSSs are not in the class of lattice-based VSSSs. In this paper, we show the well-defined polynomial representation of a VSSS based on permuting different matrices for black-white images. The necessary and sufficient condition of the existence of a VSSS based on permuting different matrices can be obtained from the proposed polynomial representation. This condition is useful for constructing a good VSSS. We also point out that without additional data, it is possible to achieve member verification by using a VSSS. Using the proposed polynomial representation, the probability of detecting a cheater is analyzed.

In this letter, we propose high-speed binary to residue converters for moduli 2n, 2n 1 without using look-up table. For integration of residue arithmetic circuit using a signed-digit (SD) number representation with ordinary binary system, the proposed circuits carry out the efficient conversion. Using SD adders instead of ordinary adders that are used in conventional binary to residue converter, the high-speed conversion without the carry propagation can be achieved. Thus, the proposed converter is independent of the size of modulus and can speed up the binary to residue conversion. On the simulation, the conversion delay times are 1.78 ns for modulus 210-1 and 1.73 ns for modulus 210+1 under the condition of 0.6 µm CMOS technology, respectively. The active area of the proposed converter for moduli 210 1 is 335 µm325 µm.